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Statistical mechanics of polymers subject to a force

2016· article· en· W2497075689 on OpenAlexafffund
Enzo Orlandini, S G Whittington

Bibliographic record

VenueJournal of Physics A Mathematical and Theoretical · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSubject (documents)Statistical mechanicsPolymerStatistical physicsMaterials scienceComputer sciencePhysicsComposite materialWorld Wide Web

Abstract

fetched live from OpenAlex

When a polymer molecule is subjected to a force (such as a tensile force) it responds and this response gives information about the thermodynamics and structural properties of the polymer. In recent years there have been a number of experimental developments, such as atomic force microscopy and optical tweezers, that allow individual polymer molecules to be pulled in various ways. This has resulted in a renewed theoretical interest in how polymers respond to applied forces. This review will focus on some particular aspects of this field. We shall be primarily interested in tensile forces and consider various scenarios, such as pulling an adsorbed polymer from a surface and pulling a polymer from one phase to another. In order to make theoretical progress one needs a model of the polymer and we shall focus on lattice models. Our emphasis will be on exactly solvable models such as Dyck and Motzkin paths, and on rigorous results for self-avoiding walk models and some relatives, though we shall also discuss scaling theories and some selected numerical results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.262
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2016
Admission routes2
Has abstractyes

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